How startups in developing countries use data to better connect workers with jobs

Youth-led start-ups are helping to connect low- and middle-skilled workers and migrants in developing countries with employers through apps and websites. 

What's more, these companies are collecting important data that can help policymakers and officials design labor market interventions and policies. National labor market information systems can also work with companies to strengthen their own capacity to collect, process, manage, and utilize data.

S4YE invited three of these youth-led companies, HaHuJobs, Seekuur, and Huntr, to share lessons learned from taking a data-driven approach to connecting talent to jobs.

HaHuJobs, a web platform, connects workers in Ethiopia with potential employers in major cities and industrial parks. Huntr, a mobile app, matches migrant workers in the health sector with potential employers in the UAE. And web-based Seekuur supports job seekers in the Caribbean.

Here are six takeaways: 

1. Specialized job-matching platforms can provide targeted data. Huntr, as an example, facilitates the matching of trained migrants seeking employment as nurses and medical staff in the UAE labour market. The platform's targeted approach allows data collection for the healthcare sector, supporting the development of one of UAE's priority sectors. Seekuur collects data on the length of time that people stay in a given position/industry/role, the interests of job seekers, and the barriers to entry into specific career paths.
2. Data from job-matching platforms has become increasingly valuable for development and industry growth. Job-matching platforms collect valuable information on job seekers' behaviour, allowing employers and policymakers to better understand the needs of specific workers, such as people who are low-skilled. And Seekuur optimizes industries' processes by helping companies automate their HR recruitment and hiring functions. The system uses artificial intelligence to learn how to best serve other companies and job candidates.  
3. Technology can help identify and match people with disabilities. Job seekers with disabilities in developing countries face a double burden, as they are less likely to have access to adapted technology. In some cases, workers could even be unaware of a disability, which could potentially make them vulnerable to occupational injuries. HaHuJobs sees technology as an opportunity and uses a variety of tools to identify jobseekers with disabilities. For factory workers, for example, there are web-based tests for color blindness and dexterity. This allows HaHuJobs to determine the kind of work candidates are best suited for.
4. Locally managed job-matching platforms can reach workers with low digital literacy through physical registration centers. HahuJobs facilitates the registration of workers who lack internet access, or the skills and literacy level needed to create an online profile. This is done through physical regional centers across Ethiopia, where job seekers also receive CV writing and job interview preparation.
5. Technology-driven job-matching solutions need to be especially cautious about avoiding recruitment bias. Discriminatory factors in recruitment may include names, graduating schools/universities, countries or regions, and physical racial distinctions. To be objective, job-matching platforms use a computerized matching system. Huntr attempts to deal with recruitment preconceptions when recruiting migrant workers through computerized screening of job applications and skills. Seekuur's approach includes aggregating and standardizing data from candidates and hiring companies before matching them via artificial intelligence.
6. Data protection is key for such platforms. As these platforms develop more sophisticated approaches and collect increasing amounts of data from their users, they need to align with national and international data protection regulations. In Ethiopia, despite the lack of data protection policy in the country, all data collected by HaHuJobs cannot be used for other purposes other than matching, while all biometric data is kept as base 64 data, which means no images of it are stored. Users can also decide and notify HaHuJobs if they wish their data to be securely deleted from the system.

The six takeaways presented through this blog show strong potential for replicability in other countries. As countries' data protection legislations develop and data collection processes diversify, private job-matching platforms have the potential to support job seekers, avoid recruitment bias and include youth with disabilities, and with low digital literacy . The examples presented are not exhaustive and aim to provide insights from three regions on the importance of job matching platforms to advance the youth employment agenda.